vinaypattanashetti

artificial_intelligence

The complete deep learning course with projects

Bank-Customer-Churn-Prediction

Developed a machine learning model to predict customer churn using extensive exploratory data analysis (EDA) and feature engineering. Implemented and evaluated various ML techniques to enhance prediction accuracy.

Bank-Customers-Loan-Report-using-Tableau-and-SQL

This report aims to provide insights into key loan-related metrics and their changes over time. The report will help us make data-driven decisions, track our loan portfolio's health, and identify trends that can inform our lending strategies.

Churn-Risk-Assessment-in-Banking

The objective of a project is to develop an accurate churn prediction model that identifies customers at risk of leaving the product. By understanding the factors influencing churn, the bank can take preventive measures to retain valuable customers.

CNN-Transfer-learning-malaria-cell-classification

This project focuses on using Convolutional Neural Networks (CNN) and Transfer Learning techniques to classify cell images as either infected with malaria or uninfected.

Credit-Card-Financial-Dashboard-using-Power-BI

The task is to develop a comprehensive credit card weekly dashboard that provides real-time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.

Credit-Risk-Modeling-Machine-learning

This Project focuses on credit worthiness of an individual predicting whether to provide credit or not.

Customer-Lifetime-Value-Forecasting

The objective of this project is to develop an accurate CLV forecasting model that estimates the future value of each customer based on historical data. By understanding the expected lifetime value of individual policyholders, the auto insurance company can tailor its marketing efforts, retention strategies, and personalized offers.

Image-Classification-using-computer-vision

This project focused on implementing a robust image classification of flowers system using advanced deep learning models like EfficientNetB4 and ResNet101. The goal was to classify images of various flower species, including roses, daisies, dandelions, sunflowers, and tulips.

Time-Series-Project-Surface-Air-Temperature-Prediction

The primary objective of this project is to predict the surface air temperature for the next month based on historical monthly mean temperatures. By using both SARIMA and LSTM models, we aim to leverage both statistical and machine learning approaches for time series forecasting and compare their effectiveness with the XGBoost Classifier.

vinaypattanashetti/artificial_intelligence

The complete deep learning course with projects

vinaypattanashetti/Bank-Customer-Churn-Prediction

Developed a machine learning model to predict customer churn using extensive exploratory data analysis (EDA) and feature engineering. Implemented and evaluated various ML techniques to enhance prediction accuracy.

vinaypattanashetti/Bank-Customers-Loan-Report-using-Tableau-and-SQL

This report aims to provide insights into key loan-related metrics and their changes over time. The report will help us make data-driven decisions, track our loan portfolio's health, and identify trends that can inform our lending strategies.

vinaypattanashetti/Churn-Risk-Assessment-in-Banking

The objective of a project is to develop an accurate churn prediction model that identifies customers at risk of leaving the product. By understanding the factors influencing churn, the bank can take preventive measures to retain valuable customers.

vinaypattanashetti/CNN-Transfer-learning-malaria-cell-classification

This project focuses on using Convolutional Neural Networks (CNN) and Transfer Learning techniques to classify cell images as either infected with malaria or uninfected.

vinaypattanashetti/Credit-Card-Financial-Dashboard-using-Power-BI

The task is to develop a comprehensive credit card weekly dashboard that provides real-time insights into key performance metrics and trends, enabling stakeholders to monitor and analyze credit card operations effectively.

vinaypattanashetti/Credit-Risk-Modeling-Machine-learning

This Project focuses on credit worthiness of an individual predicting whether to provide credit or not.

vinaypattanashetti/Customer-Lifetime-Value-Forecasting

The objective of this project is to develop an accurate CLV forecasting model that estimates the future value of each customer based on historical data. By understanding the expected lifetime value of individual policyholders, the auto insurance company can tailor its marketing efforts, retention strategies, and personalized offers.

vinaypattanashetti/Image-Classification-using-computer-vision

This project focused on implementing a robust image classification of flowers system using advanced deep learning models like EfficientNetB4 and ResNet101. The goal was to classify images of various flower species, including roses, daisies, dandelions, sunflowers, and tulips.

vinaypattanashetti/Time-Series-Project-Surface-Air-Temperature-Prediction

The primary objective of this project is to predict the surface air temperature for the next month based on historical monthly mean temperatures. By using both SARIMA and LSTM models, we aim to leverage both statistical and machine learning approaches for time series forecasting and compare their effectiveness with the XGBoost Classifier.

vinaypattanashetti/Dow-Jones-Stocks-Sentiment-Analysis

Dow Jones Stocks Sentiment Analysis leverages NLP to evaluate news headlines, predicting stock market trends. By analyzing sentiment, the project aims to provide insights into market movements, helping investors make informed decisions based on real-time news data.

vinaypattanashetti/Dump

vinaypattanashetti/End-to-End-Employee-Churn-Prediction-using-Azure-Databricks

This project focuses on end-to-end predictive modelling solution for HR Employee Churn dataset using Azure Databricks, leveraging PySpark, MLflow and deploying the model using Databricks model serving.

vinaypattanashetti/machine_learning

vinaypattanashetti/Medical-Chatbot-using-Llama2

Creating end-to-end project of medical chatbot using generative AI involves developing a conversational agent that can assist users with medical inquiries by leveraging advanced AI models.

vinaypattanashetti/MLOps-Production-Ready-Machine-Learning-Project

End-to-End MLOps project predicting "US Visa approval status". Implementing a production-ready machine learning pipeline, including data processing, model training, deployment, and monitoring. Demonstrates best practices in MLOps for real-world application.

vinaypattanashetti/NLP-Driven-Insights-on-Financial-Services-Complaints

This end-to-end project uses NLP and Machine Learning to predict customer satisfaction and potential disputes in financial complaints, leveraging data from the CFPB website to enhance response quality and customer trust.

vinaypattanashetti/NLP-Text-Summarization

End to End NLP Project - Text Summarization

vinaypattanashetti/Object-Detection-using-YOLOv5

Developed a model that can automatically recognize traffic signs along the road. These signs include speed limit signs, yield signs, no passing signs, and more. The goal is to build smarter systems that can identify and classify these signs accurately, ultimately enhancing road safety and reducing accidents.

vinaypattanashetti/Prospective-Customer-Identification-for-Term-Deposit

Developed an effective approach for banks identifying potential customers interested in term deposits, allowing for targeted marketing rather than costly and inefficient blanket targeting.

vinaypattanashetti/Retail-Credit-Scoring-Analytics-using-Alteryx

This project aims to leverage Alteryx, a powerful data analytics platform, to develop an automated and accurate credit scoring system. By integrating various data sources and applying advanced predictive analytics, the goal is to enhance decision-making, reduce risk, and improve the overall efficiency of the credit scoring process.

vinaypattanashetti/vinaypattanashetti

AI and Machine Learning Engineer